Successful businesses often rely on the gathering, interpretation, and analysis of business data. For example, businesses may use one or more databases to store customer data, transactional data, inventory data, financial data, or operational data related to operations of manufacturing, inventory, or shipping facilities. Then, by regularly applying queries against such data, businesses may obtain corresponding query results which provide valuable information to business leaders, to thereby assist the business leaders in making successful decisions with respect to future business operations.
As one example of such query results, a key performance indicator (KPI) generally refers to a single interpreted/calculated value that is obtained from a plurality of information items (e.g., data records) of the types of databases referenced above. For example, such KPIs may be used to describe a state or value of a dedicated object or other entity in a business context. By way of more specific example, KPIs may be related to an operation of a machine or class of machines, a stop of a production line, an efficiency of a supplier, or a duration of creation of a specified product. Thus, such KPIs, and other query results obtained from the types of databases referenced above, may provide fast and valuable insight with respect to specific, discrete operations of a business.
Because such KPIs and other query results may be highly useful, various different KPIs or other query results may be developed in specific business contexts. Then, the KPIs or other query results may be periodically recalculated to obtain a current status thereof, and may be provided to a user, e.g., in the context of a dashboard or other user interface.
However, when viewing such dashboards or other user interfaces, it may be difficult or impossible for a user to recognize interdependencies or other relationships between the displayed items. For example, in illustrative and non-limiting examples, KPIs may be created over a long period of time, and/or by various different users, so that it is difficult to tell, from viewing the KPIs, which underlying factors might influence one or more of the KPIs, or whether (or to what extent) a given KPI is related to another KPI. For these and other reasons, then, conventional systems do not make optimal use of available business data, or of interpreted/calculated values obtained therefrom.